Through advancements in computing devices and computing technology, individuals can easily connect with and communicate with other individuals. Indeed, through modern computing devices and systems, individuals have access to many forms of digital communication that allow them to communicate with people across the world (e.g., through a social network). Once connected, various conventional communication systems allow an individual to communicate with an audience of users by, for example, sharing a post, updating a status, sending a message, or sharing a picture or video. While many conventional systems are effective in allowing users to connect and communicate with an audience, these conventional systems have various disadvantages.
As one example, conventional systems could improve the manner of how a user finds and discovers other users with whom to connect or communicate. To demonstrate, many conventional systems provide recommendations of other users with whom a user could potentially connect. As part of providing these recommendations, conventional communication systems often identify potential connections based on shared attributes between the user and a potential connection. However, before a conventional system can identify and analyze shared attributes of users, each user must often provide the system with multiple pieces of user profile information (e.g., connections, demographic information, personal information, interests, etc.). For example, a conventional system compares profile information between the user and potential connections to identify common attributes. Thus, as one shortcoming, conventional systems require users to first provide various pieces of information and/or use the social networking system for a period of time before the system can begin to identify and recommend potential connections
As another shortcoming, the recommendation quality of potential connections varies based on the amount and type of information provided by the user (as well as the other users). Indeed, even with established users who have provided substantial amounts of information, because users are subjective in their preferences, conventional systems often identify potential connections with whom users do not want to connect and view as low-quality or undesirable connections.
As an additional shortcoming, the process of correlating various pieces of information between users to determine potential connections for a user is complex and resource intensive. For example, conventional systems attempt to correlate, factor, regress, and weight information provided by multiple users of a social networking system to determine how compatible users are to each other as part of the recommendation process. Occasionally, users provide subjective and/or misleading information, which further distorts the process of identifying quality potential connections.
Accordingly, these and several other disadvantages, shortcomings, and drawbacks exist with regard to conventional systems.